Muqdad Alhijjaj^1,2 , Ahmed AA Alsaad¹, Mustafa Sabah Taha³

¹Department of Pharmaceutics, College of Pharmacy, University of Basrah, 61004 Basrah,; ²Department of Pharmaceutics, College of Pharmacy, Al-Kunooze University, 61026 Basrah,; ³Missan Oil Training Institute, Ministry of Oil, 61026 Missan, Iraq.

For correspondence:-  Muqdad Alhijjaj   Email: muqdad.mousa@uobasrah.edu.iq

Received: 13 July 2026        Accepted: 21 October 2026        Published: 31 October 2026

Citation: Alhijjaj M, Alsaad AA, Taha MS. Multi-objective optimization for quality control in 3D printed pharmaceuticals: ensuring precision in drug layering. Trop J Pharm Res 2026; 25(10):1333-1343 doi: 10.4314/tjpr.v25i10.1

© 2026 The authors.
This is an Open Access article that uses a funding model which does not charge readers or their institutions for access and distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) and the Budapest Open Access Initiative (http://www.budapestopenaccessinitiative.org/read), which permit unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited..

Abstract

Purpose: To develop an optimized framework for quality control of 3D printing in pharmaceutical processes. Methods: The framework integrated five key quality parameters: active pharmaceutical ingredient (API) content accuracy, uniformity, mechanical strength, production time, and dissolution profile. Results: The proposed framework identified Pareto-optimal solutions where no objective can be improved without degrading at least one other. Solution 1 showed better content accuracy and uniformity, and superior mechanical properties at all infill densities, with about 15 % higher mechanical properties compared to solutions 2 and 3. Solution 1 had longer build times, especially at small layer heights, compared to solution 3. Solution 1 also showed good content uniformity but had significantly lower dissolution-profile accuracy and longer production time. Furthermore, none of these solutions has a dissolution profile that is very close to the target. Conclusions: Evaluation of the proposed framework highlighted efficient identification of diverse parameter combinations that simultaneously satisfy multiple quality requirements; hence, the framework may inform manufacturing decisions based on specific priorities and regulatory constraints.

Keywords: Content uniformity, Drug layering precision, Multi-objective optimization, Pareto optimization, Pharmaceutical 3D printing

Impact Factor
Thompson Reuters (ISI): 0.6 (2023)
H-5 index (Google Scholar): 49 (2023)